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Ren Y, Yue Y, Li X, Weng S, Xu H, Liu L, Cheng Q, Luo P, Zhang T, Liu Z, Han X. Proteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy. Int Immunopharmacol 2024; 142:113147. [PMID: 39270345 DOI: 10.1016/j.intimp.2024.113147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 08/11/2024] [Accepted: 09/08/2024] [Indexed: 09/15/2024]
Abstract
Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described.
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Affiliation(s)
- Yuqing Ren
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yi Yue
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xinyang Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hui Xu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Long Liu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Tengfei Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China.
| | - Zaoqu Liu
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Institute of Zhengzhou University, Zhengzhou, Henan 450052, China; Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan 450052, China.
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Wang CR, Zenaidee MA, Snel MF, Pukala TL. Exploring Top-Down Mass Spectrometric Approaches To Probe Forest Cobra ( Naja melanoleuca) Venom Proteoforms. J Proteome Res 2024; 23:4601-4613. [PMID: 39231368 DOI: 10.1021/acs.jproteome.4c00486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/06/2024]
Abstract
Snake venoms are comprised of bioactive proteins and peptides that facilitate severe snakebite envenomation symptoms. A comprehensive understanding of venom compositions and the subtle heterogeneity therein is important. While bottom-up proteomics has been the well-established approach to catalogue venom compositions, top-down proteomics has emerged as a complementary strategy to characterize venom heterogeneity at the intact protein level. However, top-down proteomics has not been as widely implemented in the snake venom field as bottom-up proteomics, with various emerging top-down methods yet to be developed for venom systems. Here, we have explored three main top-down mass spectrometry methodologies in a proof-of-concept study to characterize selected three-finger toxin and phospholipase A2 proteoforms from the forest cobra (Naja melanoleuca) venom. We demonstrated the utility of a data-independent acquisition mode "MSE" for untargeted fragmentation on a chromatographic time scale and its improvement in protein sequence coverage compared to conventional targeted tandem mass spectrometry analysis. We also showed that protein identification can be further improved using a hybrid fragmentation approach, combining electron-capture dissociation and collision-induced dissociation. Lastly, we reported the promising application of multifunctional cyclic ion mobility separation and post-ion mobility fragmentation on snake venom proteins for the first time.
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Affiliation(s)
- C Ruth Wang
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Muhammad A Zenaidee
- Australian Proteome Analysis Facility, Macquarie University, Macquarie Park, NSW 2109, Australia
| | - Marten F Snel
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
- Proteomics, Metabolomics and MS-Imaging Core Facility, South Australian Health and Medical Research Institute, Adelaide, SA 5005, Australia
| | - Tara L Pukala
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
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Hsiao Y, Zhang H, Li GX, Deng Y, Yu F, Valipour Kahrood H, Steele JR, Schittenhelm RB, Nesvizhskii AI. Analysis and Visualization of Quantitative Proteomics Data Using FragPipe-Analyst. J Proteome Res 2024; 23:4303-4315. [PMID: 39254081 DOI: 10.1021/acs.jproteome.4c00294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows, including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.
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Affiliation(s)
- Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Haijian Zhang
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Yamei Deng
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Hossein Valipour Kahrood
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
- Monash Genomics & Bioinformatics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Joel R Steele
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ralf B Schittenhelm
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
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Qin W, Wu Y, Gao W, Wang Y. Application of molecular networking to improve the compound annotation in liquid chromatography-mass spectrometry-based metabolomics analysis: A case study of Bupleuri radix. PHYTOCHEMICAL ANALYSIS : PCA 2024; 35:1695-1703. [PMID: 38923688 DOI: 10.1002/pca.3412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024]
Abstract
INTRODUCTION Compound annotation is always a challenging step in metabolomics studies. The molecular networking strategy has been developed recently to organize the relationship between compounds as a network based on their tandem mass (MS2) spectra similarity, which can be used to improve compound annotation in metabolomics analysis. OBJECTIVE This study used Bupleuri Radix from different geographic areas to evaluate the performance of molecular networking strategy for compound annotation in liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. METHODOLOGY The Bupleuri Radix extract was analyzed by LC-quadrupole time-of-flight MS under MSe acquisition mode. After raw data preprocessing, the resulting dataset was used for statistical analysis, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The chemical makers related to the sample growth place were selected using variable importance in projection (VIP) > 2, fold change (FC) > 2, and p < 0.05. The molecular networking analysis was applied to conduct the compound annotation. RESULTS The score plots of PCA showed that the samples were classified into two clusters depending on their growth place. Then, the PLS-DA model was constructed to explore the chemical changes of the samples further. Sixteen compounds were selected as chemical makers and tentatively annotated by the feature-based molecular networking (FBMN) analysis. CONCLUSION The results showed that the molecular networking method fully exploits the MS information and is a promising tool for facilitating compound annotation in metabolomics studies. However, the software used for feature extraction influenced the results of library searching and molecular network construction, which need to be taken into account in future studies.
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Affiliation(s)
- Weibo Qin
- School of Pharmaceutical Sciences, Changchun University of Chinese Medicine, Changchun, China
| | - Yi Wu
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun, China
| | - Wenyi Gao
- School of Pharmaceutical Sciences, Changchun University of Chinese Medicine, Changchun, China
| | - Yang Wang
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun, China
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Kabatnik S, Post F, Drici L, Bartels AS, Strauss MT, Zheng X, Madsen GI, Mund A, Rosenberger FA, Moreira J, Mann M. Spatial characterization and stratification of colorectal adenomas by deep visual proteomics. iScience 2024; 27:110620. [PMID: 39252972 PMCID: PMC11381895 DOI: 10.1016/j.isci.2024.110620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 05/13/2024] [Accepted: 07/26/2024] [Indexed: 09/11/2024] Open
Abstract
Colorectal adenomas (CRAs) are potential precursor lesions to adenocarcinomas, currently classified by morphological features. We aimed to establish a molecular feature-based risk allocation framework toward improved patient stratification. Deep visual proteomics (DVP) is an approach that combines image-based artificial intelligence with automated microdissection and ultra-high sensitive mass spectrometry. Here, we used DVP on formalin-fixed, paraffin-embedded (FFPE) CRA tissues from nine male patients, immunohistologically stained for caudal-type homeobox 2 (CDX2), a protein implicated in colorectal cancer, enabling the characterization of cellular heterogeneity within distinct tissue regions and across patients. DVP identified DMBT1, MARCKS, and CD99 as protein markers linked to recurrence, suggesting their potential for risk assessment. It also detected a metabolic shift to anaerobic glycolysis in cells with high CDX2 expression. Our findings underscore the potential of spatial proteomics to refine early stage detection and contribute to personalized patient management strategies and provided novel insights into metabolic reprogramming.
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Affiliation(s)
- Sonja Kabatnik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Frederik Post
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Lylia Drici
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Annette Snejbjerg Bartels
- Precision Cancer Medicine Laboratory, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maximilian T Strauss
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Xiang Zheng
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Gunvor I Madsen
- Department of Pathology, Odense University Hospital, Odense, Denmark
| | - Andreas Mund
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Florian A Rosenberger
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - José Moreira
- Precision Cancer Medicine Laboratory, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
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6
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Elsayyid M, Tanis JE, Yu Y. In-cell processing enables rapid and in-depth proteome analysis of low-input Caenorhabditis elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.18.613705. [PMID: 39345438 PMCID: PMC11429863 DOI: 10.1101/2024.09.18.613705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Caenorhabditis elegans is a widely used genetic model organism, however, the worm cuticle complicates extraction of intracellular proteins, a prerequisite for typical bottom-up proteomics. Conventional physical disruption procedures are not only time-consuming, but can also cause significant sample loss, making it difficult to perform proteomics with low-input samples. Here, for the first time, we present an on-filter in-cell (OFIC) processing approach, which can digest C. elegans proteins directly in the cells of the organism after methanol fixation. With OFIC processing and single-shot LCMS analysis, we identified over 9,400 proteins from a sample of only 200 worms, the largest C. elegans proteome reported to date that did not require fractionation or enrichment. We systematically evaluated the performance of the OFIC approach by comparing it with conventional lysis-based methods. Our data suggest equivalent and unbiased performance of OFIC processing for C. elegans proteome identification and quantitation. We further evaluated the OFIC approach with even lower input samples, then used this method to determine how the proteome is impacted by loss of superoxide dismutase sod-1, the ortholog of human SOD-1, a gene associated with amyotrophic lateral sclerosis (ALS). Analysis of 8,800 proteins from only 50 worms as the initial input showed that loss of sod-1 affects the abundance of proteins required for stress response, ribosome biogenesis, and metabolism. In conclusion, our streamlined OFIC approach, which can be broadly applied to other systems, minimizes sample loss while offering the simplest workflow reported to date for C. elegans proteomics analysis.
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Affiliation(s)
- Malek Elsayyid
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Jessica E. Tanis
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Yanbao Yu
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, 19716, USA
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Wang S, Di Y, Yang Y, Salovska B, Li W, Hu L, Yin J, Shao W, Zhou D, Cheng J, Liu D, Yang H, Liu Y. PTMoreR-enabled cross-species PTM mapping and comparative phosphoproteomics across mammals. CELL REPORTS METHODS 2024; 4:100859. [PMID: 39255793 PMCID: PMC11440062 DOI: 10.1016/j.crmeth.2024.100859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 05/13/2024] [Accepted: 08/15/2024] [Indexed: 09/12/2024]
Abstract
To support PTM proteomic analysis and annotation in different species, we developed PTMoreR, a user-friendly tool that considers the surrounding amino acid sequences of PTM sites during BLAST, enabling a motif-centric analysis across species. By controlling sequence window similarity, PTMoreR can map phosphoproteomic results between any two species, perform site-level functional enrichment analysis, and generate kinase-substrate networks. We demonstrate that the majority of real P-sites in mice can be inferred from experimentally derived human P-sites with PTMoreR mapping. Furthermore, the compositions of 129 mammalian phosphoproteomes can also be predicted using PTMoreR. The method also identifies cross-species phosphorylation events that occur on proteins with an increased tendency to respond to the environmental factors. Moreover, the classic kinase motifs can be extracted across mammalian species, offering an evolutionary angle for refining current motifs. PTMoreR supports PTM proteomics in non-human species and facilitates quantitative phosphoproteomic analysis.
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Affiliation(s)
- Shisheng Wang
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yi Di
- Yale Cancer Biology Institute, Yale University, West Haven, CT 06516, USA
| | - Yin Yang
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, CT 06516, USA
| | - Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT 06516, USA
| | - Liqiang Hu
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Jiahui Yin
- Information Research Institute, Tongji University, Shanghai 200092, China
| | - Wenguang Shao
- State Key Laboratory of Microbial Metabolism, School of Life Science & Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Dong Zhou
- Department of Medicine, Division of Nephrology, University of Connecticut School of Medicine, Farmington, CT 06030, USA
| | - Jingqiu Cheng
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Dan Liu
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China; State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Hao Yang
- Department of Pulmonary and Critical Care Medicine, Proteomics-Metabolomics Analysis Platform, and NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu 610041, China.
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT 06516, USA; Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Informatics & Data Science, Yale Univeristy School of Medicine, New Haven, CT 06510, USA.
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Huo S, Nie S, Cong Y, Wang S, Li N. In-Depth Host Cell Protein Analysis and Viral Protein Impurity Monitoring in Adeno-Associated Virus-Based Gene Therapy Products Using Optimized Wide Window Data-Dependent Acquisition Method. Anal Chem 2024. [PMID: 39263887 DOI: 10.1021/acs.analchem.4c02400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2024]
Abstract
Compared to other protein therapeutics, there is currently limited knowledge about the residual host cell proteins (HCPs) in adeno-associated virus (AAV)-based gene therapy products. This is primarily due to the lack of a robust and sensitive mass spectrometry-based method for HCP analysis in AAV samples. Existing liquid chromatography-mass spectrometry methods used for analyzing HCPs in therapeutic monoclonal antibodies (mAbs) often cannot be directly applied to AAVs, due to some unique characteristics of AAV samples encountered during their development such as limited sample availability/protein concentration and the presence of surfactants. In this study, we have developed a novel workflow for robust and in-depth HCP analysis of AAV samples by combining wide-window data-dependent acquisition for improved low-abundance HCP detection with single-pot, solid-phase-enhanced sample preparation (SP3) for low-input sample preparation. Using this newly developed method, we were able to detect more than 650 HCPs in a commercial AAV1 sample with a high quantitative reproducibility. This represents a greater than 5-fold increase in HCP protein identification compared to an in-solution digestion method followed by traditional data-dependent acquisition. Similar benefits can also be achieved for other AAV serotypes that were produced internally and purified through different processes. The detection limit of this method is as low as 0.06 ng/mL, enabling more comprehensive HCP coverage in AAV samples. Moreover, for the first time, we have identified several process-related viral proteins, such as Rep 78 and E4. These proteins need to be closely monitored during AAV process development as they may present a greater risk for immunogenicity compared to HCPs that are derived from human HEK293 cells.
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Affiliation(s)
- Shihan Huo
- Analytical Chemistry Group, Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, New York 10591-6707, United States
| | - Song Nie
- Analytical Chemistry Group, Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, New York 10591-6707, United States
| | - Yongzheng Cong
- Analytical Chemistry Group, Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, New York 10591-6707, United States
| | - Shunhai Wang
- Analytical Chemistry Group, Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, New York 10591-6707, United States
| | - Ning Li
- Analytical Chemistry Group, Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, New York 10591-6707, United States
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9
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Shi M, Huang C, Chen R, Chen DDY, Yan B. A New Evaluation Metric for Quantitative Accuracy of LC-MS/MS-Based Proteomics with Data-Independent Acquisition. J Proteome Res 2024; 23:3780-3790. [PMID: 39193824 DOI: 10.1021/acs.jproteome.4c00088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2024]
Abstract
Data-independent acquisition (DIA) has improved the identification and quantitation coverage of peptides and proteins in liquid chromatography-tandem mass spectrometry-based proteomics. However, different DIA data-processing tools can produce very different identification and quantitation results for the same data set. Currently, benchmarking studies of DIA tools are predominantly focused on comparing the identification results, while the quantitative accuracy of DIA measurements is acknowledged to be important but insufficiently investigated, and the absence of suitable metrics for comparing quantitative accuracy is one of the reasons. A new metric is proposed for the evaluation of quantitative accuracy to avoid the influence of differences in false discovery rate control stringency. The part of the quantitation results with high reliability was acquired from each DIA tool first, and the quantitative accuracy was evaluated by comparing quantification error rates at the same number of accurate ratios. From the results of four benchmark data sets, the proposed metric was shown to be more sensitive to discriminating the quantitative performance of DIA tools. Moreover, the DIA tools with advantages in quantitative accuracy were consistently revealed by this metric. The proposed metric can also help researchers in optimizing algorithms of the same DIA tool and sample preprocessing methods to enhance quantitative accuracy.
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Affiliation(s)
- Mengtian Shi
- College of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou 310053, China
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
| | - Chiyuan Huang
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
| | - Renhui Chen
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
| | - David Da Yong Chen
- Department of Chemistry, University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Binjun Yan
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
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10
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Thangudu RR, Holck M, Singhal D, Pilozzi A, Edwards N, Rudnick PA, Domagalski MJ, Chilappagari P, Ma L, Xin Y, Le T, Nyce K, Chaudhary R, Ketchum KA, Maurais A, Connolly B, Riffle M, Chambers MC, MacLean B, MacCoss MJ, McGarvey PB, Basu A, Otridge J, Casas-Silva E, Venkatachari S, Rodriguez H, Zhang X. NCI's Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis through Cross-Referencing with Genomic and Imaging Data. CANCER RESEARCH COMMUNICATIONS 2024; 4:2480-2488. [PMID: 39225545 DOI: 10.1158/2767-9764.crc-24-0243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/22/2024] [Accepted: 08/29/2024] [Indexed: 09/04/2024]
Abstract
Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement and widespread availability of high-throughput proteomic technologies, the generation of large-scale proteomic data has become more common in cancer research, and there is a growing need for resources that support the sharing and integration of multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen, and experimental and workflow annotations that are crucial for data interpretation and reanalysis. The need to integrate, analyze, and share these data has led to the development of NCI's Proteomic Data Commons (PDC), accessible at https://pdc.cancer.gov. As a specialized repository within the NCI Cancer Research Data Commons (CRDC), PDC enables researchers to locate and analyze proteomic data from various cancer types and connect with genomic and imaging data available for the same samples in other CRDC nodes. Presently, PDC houses annotated data from more than 160 datasets across 19 cancer types, generated by several large-scale cancer research programs with cohort sizes exceeding 100 samples (tumor and associated normal when available). In this article, we review the current state of PDC in cancer research, discuss the opportunities and challenges associated with data sharing in proteomics, and propose future directions for the resource. SIGNIFICANCE The Proteomic Data Commons (PDC) plays a crucial role in advancing cancer research by providing a centralized repository of high-quality cancer proteomic data, enriched with extensive clinical annotations. By integrating and cross-referencing with complementary genomic and imaging data, the PDC facilitates multi-omics analyses, driving comprehensive insights, and accelerating discoveries across various cancer types.
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Affiliation(s)
| | | | | | | | | | - Paul A Rudnick
- Spectragen Informatics LLC, Bainbridge Island, Washington
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Esmeralda Casas-Silva
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Rockville, Maryland
| | | | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, Maryland
| | - Xu Zhang
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, Maryland
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11
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Fayyaz AU, Eltony M, Prokop LJ, Koepp KE, Borlaug BA, Dasari S, Bois MC, Margulies KB, Maleszewski JJ, Wang Y, Redfield MM. Pathophysiological insights into HFpEF from studies of human cardiac tissue. Nat Rev Cardiol 2024:10.1038/s41569-024-01067-1. [PMID: 39198624 DOI: 10.1038/s41569-024-01067-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/18/2024] [Indexed: 09/01/2024]
Abstract
Heart failure with preserved ejection fraction (HFpEF) is a major, worldwide health-care problem. Few therapies for HFpEF exist because the pathophysiology of this condition is poorly defined and, increasingly, postulated to be diverse. Although perturbations in other organs contribute to the clinical profile in HFpEF, altered cardiac structure, function or both are the primary causes of this heart failure syndrome. Therefore, studying myocardial tissue is fundamental to improve pathophysiological insights and therapeutic discovery in HFpEF. Most studies of myocardial changes in HFpEF have relied on cardiac tissue from animal models without (or with limited) confirmatory studies in human cardiac tissue. Animal models of HFpEF have evolved based on theoretical HFpEF aetiologies, but these models might not reflect the complex pathophysiology of human HFpEF. The focus of this Review is the pathophysiological insights gained from studies of human HFpEF myocardium. We outline the rationale for these studies, the challenges and opportunities in obtaining myocardial tissue from patients with HFpEF and relevant comparator groups, the analytical approaches, the pathophysiological insights gained to date and the remaining knowledge gaps. Our objective is to provide a roadmap for future studies of cardiac tissue from diverse cohorts of patients with HFpEF, coupling discovery biology with measures to account for pathophysiological diversity.
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Affiliation(s)
- Ahmed U Fayyaz
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Muhammad Eltony
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA
| | - Larry J Prokop
- Mayo Clinic College of Medicine and Science, Library Reference Service, Rochester, MN, USA
| | - Katlyn E Koepp
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA
| | - Barry A Borlaug
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA
| | - Surendra Dasari
- Mayo Clinic College of Medicine and Science, Computational Biology, Rochester, MN, USA
| | - Melanie C Bois
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Kenneth B Margulies
- Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joesph J Maleszewski
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Ying Wang
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA
| | - Margaret M Redfield
- Department of Cardiovascular Disease, Division of Circulatory Failure, Mayo Clinic, Rochester, MN, USA.
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12
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Sin WC, Liu J, Zhong JY, Lam HM, Lim BL. Comparative proteomics analysis of root and nodule mitochondria of soybean. PLANT, CELL & ENVIRONMENT 2024. [PMID: 39007421 DOI: 10.1111/pce.15026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 06/18/2024] [Accepted: 06/21/2024] [Indexed: 07/16/2024]
Abstract
Legumes perform symbiotic nitrogen fixation through rhizobial bacteroids housed in specialised root nodules. The biochemical process is energy-intensive and consumes a huge carbon source to generate sufficient reducing power. To maintain the symbiosis, malate is supplied by legume nodules to bacteroids as their major carbon and energy source in return for ammonium ions and nitrogenous compounds. To sustain the carbon supply to bacteroids, nodule cells undergo drastic reorganisation of carbon metabolism. Here, a comprehensive quantitative comparison of the mitochondrial proteomes between root nodules and uninoculated roots was performed using data-independent acquisition proteomics, revealing the modulations in nodule mitochondrial proteins and pathways in response to carbon reallocation. Corroborated our findings with that from the literature, we believe nodules preferably allocate cytosolic phosphoenolpyruvates towards malate synthesis in lieu of pyruvate synthesis, and nodule mitochondria prefer malate over pyruvate as the primary source of NADH for ATP production. Moreover, the differential regulation of respiratory chain-associated proteins suggests that nodule mitochondria could enhance the efficiencies of complexes I and IV for ATP synthesis. This study highlighted a quantitative proteomic view of the mitochondrial adaptation in soybean nodules.
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Affiliation(s)
- Wai-Ching Sin
- School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Jinhong Liu
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong, China
| | - Jia Yi Zhong
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong, China
| | - Hon-Ming Lam
- School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Boon Leong Lim
- School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong, China
- State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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13
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Humphries EM, Xavier D, Ashman K, Hains PG, Robinson PJ. High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH. J Proteome Res 2024; 23:2355-2366. [PMID: 38819404 DOI: 10.1021/acs.jproteome.4c00010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 μg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.
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Affiliation(s)
- Erin M Humphries
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Keith Ashman
- Sciex, 96 Ricketts Road,Mount Waverley, Victoria 3149, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales 2145, Australia
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14
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Rincon Pabon JP, Akbar Z, Politis A. MSe Collision Energy Optimization for the Analysis of Membrane Proteins Using HDX-cIMS. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1383-1389. [PMID: 38842540 PMCID: PMC11228973 DOI: 10.1021/jasms.4c00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 05/09/2024] [Accepted: 06/05/2024] [Indexed: 06/07/2024]
Abstract
Hydrogen/deuterium exchange mass spectrometry (HDX-MS) has evolved as an essential technique in structural proteomics. The use of ion mobility separation (IMS) coupled to HDX-MS has increased the applicability of the technique to more complex systems and has been shown to improve data quality and robustness. The first step when running any HDX-MS workflow is to confirm the sequence and retention time of the peptides resulting from the proteolytic digestion of the nondeuterated protein. Here, we optimized the collision energy ramp of HDMSE experiments for membrane proteins using a Waters SELECT SERIES cIMS-QTOF system following an HDX workflow using Phosphorylase B, XylE transporter, and Smoothened receptor (SMO) as model systems. Although collision energy (CE) ramp 10-50 eV gave the highest amount of positive identified peptides when using Phosphorylase B, XylE, and SMO, results suggest optimal CE ramps are protein specific, and different ramps can produce a unique set of peptides. We recommend cIMS users use different CE ramps in their HDMSE experiments and pool the results to ensure maximum peptide identifications. The results show how selecting an appropriate CE ramp can change the sequence coverage of proteins ranging from 4 to 94%.
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Affiliation(s)
- Juan Pablo Rincon Pabon
- Faculty of Biology, Medicine and Health, Division of Molecular and Cellular Function, The University of Manchester, Manchester M13 9PT, U.K
- Manchester Institute of Biotechnology, University of Manchester, Princess Street, Manchester M1 7DN, U.K
| | - Zulaikha Akbar
- Faculty of Biology, Medicine and Health, Division of Molecular and Cellular Function, The University of Manchester, Manchester M13 9PT, U.K
- Manchester Institute of Biotechnology, University of Manchester, Princess Street, Manchester M1 7DN, U.K
| | - Argyris Politis
- Faculty of Biology, Medicine and Health, Division of Molecular and Cellular Function, The University of Manchester, Manchester M13 9PT, U.K
- Manchester Institute of Biotechnology, University of Manchester, Princess Street, Manchester M1 7DN, U.K
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15
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Fan Z, Hu Y, Chen L, Lu X, Zheng L, Ma D, Li Z, Zhong J, Lin L, Zhang S, Zhang G. Multiplatform tear proteomic profiling reveals novel non-invasive biomarkers for diabetic retinopathy. Eye (Lond) 2024; 38:1509-1517. [PMID: 38336992 PMCID: PMC11126564 DOI: 10.1038/s41433-024-02938-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 12/19/2023] [Accepted: 01/16/2024] [Indexed: 02/12/2024] Open
Abstract
OBJECTIVES To investigate a comprehensive proteomic profile of the tear fluid in patients with diabetic retinopathy (DR) and further define non-invasive biomarkers. METHODS A cross-sectional, multicentre study that includes 46 patients with DR, 28 patients with diabetes mellitus (DM), and 30 healthy controls (HC). Tear samples were collected with Schirmer strips. As for the discovery set, data-independent acquisition mass spectrometry was used to characterize the tear proteomic profile. Differentially expressed proteins between groups were identified, with gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis further developed. Classifying performance of biomarkers for distinguishing DR from DM was compared by the combination of three machine-learning algorithms. The selected biomarker panel was tested in the validation cohort using parallel reaction monitoring mass spectrometry. RESULTS Among 3364 proteins quantified, 235 and 88 differentially expressed proteins were identified for DR when compared to HC and DM, respectively, which were fundamentally related to retina homeostasis, inflammation and immunity, oxidative stress, angiogenesis and coagulation, metabolism, and cellular adhesion processes. The biomarker panel consisting of NAD-dependent protein deacetylase sirtuin-2 (SIR2), amine oxidase [flavin-containing] B (AOFB), and U8 snoRNA-decapping enzyme (NUD16) exhibited the best diagnostic performance in discriminating DR from DM, with AUCs of 0.933 and 0.881 in the discovery and validation set, respectively. CONCLUSIONS Tear protein dysregulation is comprehensively revealed to be associated with DR onset. The combination of tear SIR2, AOFB, and NUD16 can be a novel potential approach for non-invasive detection or pre-screening of DR. CLINICAL TRIAL REGISTRATION Chinese Clinical Trial Registry Identifier: ChiCTR2100054263. https://www.chictr.org.cn/showproj.html?proj=143177 . Date of registration: 2021/12/12.
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Affiliation(s)
- Zixin Fan
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
- International Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong, 518040, China
| | - Yarou Hu
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
| | - Laijiao Chen
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
| | - Xiaofeng Lu
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
| | - Lei Zheng
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
| | - Dahui Ma
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China
| | - Zhiqiang Li
- Shenmei Eye Hospital, Meizhou, Guangdong, 514000, China
| | - Jingwen Zhong
- Shenmei Eye Hospital, Meizhou, Guangdong, 514000, China
| | - Lin Lin
- Southern University of Science and Technology, Shenzhen, Guangdong, 518040, China
| | - Sifan Zhang
- New York University, New York, NY 10003, USA
| | - Guoming Zhang
- Shenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, 518040, China.
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16
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Zheng X, Zhou C, Hu Y, Xu S, Hu L, Li B, Zhao X, Li Q, Tang X, Huang K. Mass Spectrometry-Based Proteomics Analysis Unveils PTPRS Inhibits Proliferation and Inflammatory Response of Keratinocytes in Psoriasis. Inflammation 2024:10.1007/s10753-024-02044-z. [PMID: 38739342 DOI: 10.1007/s10753-024-02044-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/25/2024] [Accepted: 05/02/2024] [Indexed: 05/14/2024]
Abstract
In this study, we used data-independent acquisition-mass spectrometry (DIA-MS) to analyze the serum proteome in psoriasis vulgaris (PsO). The serum proteomes of seven healthy controls and eight patients with PsO were analyzed using DIA-MS. Weighted gene co-expression network analysis was used to identify differentially expressed proteins (DEPs) that were closely related to PsO. Hub proteins of PsO were also identified. The Proteomics Drug Atlas 2023 was used to predict candidate hub protein drugs. To confirm the expression of the candidate factor, protein tyrosine phosphatase receptor S (PTPRS), in psoriatic lesions and the psoriatic keratinocyte model, immunohistochemical staining, quantitative real-time polymerase chain reaction, and western blotting were performed. A total of 129 DEPs were found to be closely related to PsO. The hub proteins for PsO were PVRL1, FGFR1, PTPRS, CDH2, CDH1, MCAM, and THY1. Five candidate hub protein drugs were identified: encorafenib, leupeptin, fedratinib, UNC 0631, and SCH 530348. PTPRS was identified as a common pharmacological target for these five drugs. PTPRS knockdown in keratinocytes promoted the proliferation and expression of IL-1α, IL-1β, IL-23A, TNF-α, MMP9, CXCL8, and S100A9. PTPRS expression was decreased in PsO, and PTPRS negatively regulated PsO. PTPRS may be involved in PsO pathogenesis through the inhibition of keratinocyte proliferation and inflammatory responses and is a potential treatment target for PsO.
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Affiliation(s)
- Xuyu Zheng
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Cui Zhou
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Yulian Hu
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Shihao Xu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Li Hu
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Biyu Li
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Xiaoqin Zhao
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Qian Li
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Xin Tang
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China
| | - Kun Huang
- Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
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17
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Ha A, Khoo A, Ignatchenko V, Khan S, Waas M, Vesprini D, Liu SK, Nyalwidhe JO, Semmes OJ, Boutros PC, Kislinger T. Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine. J Proteome Res 2024; 23:1768-1778. [PMID: 38580319 PMCID: PMC11077481 DOI: 10.1021/acs.jproteome.4c00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/02/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.
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Affiliation(s)
- Annie Ha
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Amanda Khoo
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Vladimir Ignatchenko
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Shahbaz Khan
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Matthew Waas
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
| | - Danny Vesprini
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Stanley K. Liu
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Department
of Radiation Oncology, University of Toronto, Toronto, Ontario M5T 1P5, Canada
- Odette
Cancer Research Program, Sunnybrook Research
Institute, Toronto, Ontario M4N 3M5, Canada
| | - Julius O. Nyalwidhe
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Oliver John Semmes
- Leroy
T. Canoles Jr. Cancer Research Center, Eastern
Virginia Medical School, Norfolk, Virginia 23501, United States
- Department
of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23501, United States
| | - Paul C. Boutros
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
- Department
of Urology, University of California, Los
Angeles, Los Angeles, California 90095, United States
- Institute
for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095, United States
- Eli
and Edythe Broad Stem Cell Research Center, University of California, Los
Angeles, California 90095, United States
- Broad
Stem Cell Research Center, University of
California, Los Angeles, California 90095, United States
- Jonsson
Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90024, United States
- Department
of Human Genetics, University of California,
Los Angeles, Los Angeles, California 90095, United States
| | - Thomas Kislinger
- Department
of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Princess
Margaret Cancer Centre, University Health
Network, Toronto, Ontario M5G 1L7, Canada
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18
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Reder A, Hentschker C, Steil L, Gesell Salazar M, Hammer E, Dhople VM, Sura T, Lissner U, Wolfgramm H, Dittmar D, Harms M, Surmann K, Völker U, Michalik S. MassSpecPreppy-An end-to-end solution for automated protein concentration determination and flexible sample digestion for proteomics applications. Proteomics 2024; 24:e2300294. [PMID: 37772677 DOI: 10.1002/pmic.202300294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/13/2023] [Accepted: 09/14/2023] [Indexed: 09/30/2023]
Abstract
In proteomics, fast, efficient, and highly reproducible sample preparation is of utmost importance, particularly in view of fast scanning mass spectrometers enabling analyses of large sample series. To address this need, we have developed the web application MassSpecPreppy that operates on the open science OT-2 liquid handling robot from Opentrons. This platform can prepare up to 96 samples at once, performing tasks like BCA protein concentration determination, sample digestion with normalization, reduction/alkylation and peptide elution into vials or loading specified peptide amounts onto Evotips in an automated and flexible manner. The performance of the developed workflows using MassSpecPreppy was compared with standard manual sample preparation workflows. The BCA assay experiments revealed an average recovery of 101.3% (SD: ± 7.82%) for the MassSpecPreppy workflow, while the manual workflow had a recovery of 96.3% (SD: ± 9.73%). The species mix used in the evaluation experiments showed that 94.5% of protein groups for OT-2 digestion and 95% for manual digestion passed the significance thresholds with comparable peptide level coefficient of variations. These results demonstrate that MassSpecPreppy is a versatile and scalable platform for automated sample preparation, producing injection-ready samples for proteomics research.
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Affiliation(s)
- Alexander Reder
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Christian Hentschker
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Leif Steil
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Manuela Gesell Salazar
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Elke Hammer
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Vishnu M Dhople
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Thomas Sura
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Ulrike Lissner
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Hannes Wolfgramm
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Denise Dittmar
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Marco Harms
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Kristin Surmann
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Uwe Völker
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Stephan Michalik
- Interfaculty Institute of Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
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19
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Gao Y, Kim H, Kitata RB, Lin TT, Swensen AC, Shi T, Liu T. Multiplexed quantitative proteomics in prostate cancer biomarker development. Adv Cancer Res 2024; 161:31-69. [PMID: 39032952 DOI: 10.1016/bs.acr.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.
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Affiliation(s)
- Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Hyeyoon Kim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Reta Birhanu Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Tai-Tu Lin
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Adam C Swensen
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States.
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20
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Coorssen JR, Padula MP. Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience. Proteomes 2024; 12:14. [PMID: 38651373 PMCID: PMC11036260 DOI: 10.3390/proteomes12020014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 04/25/2024] Open
Abstract
With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.
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Affiliation(s)
- Jens R. Coorssen
- Department of Biological Sciences, Faculty of Mathematics and Science, Brock University, St. Catharines, ON L2S 3A1, Canada
- Institute for Globally Distributed Open Research and Education (IGDORE), St. Catharines, ON L2N 4X2, Canada
| | - Matthew P. Padula
- School of Life Sciences and Proteomics, Lipidomics and Metabolomics Core Facility, Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia
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21
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Shrestha HK, Lee D, Wu Z, Wang Z, Fu Y, Wang X, Serrano GE, Beach TG, Peng J. Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry. J Proteome Res 2024; 23:1221-1231. [PMID: 38507900 PMCID: PMC11065482 DOI: 10.1021/acs.jproteome.3c00685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.
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Affiliation(s)
- Him K. Shrestha
- Departments of Structural Biology and Developmental Neurobiology
| | - DongGeun Lee
- Departments of Structural Biology and Developmental Neurobiology
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology
| | - Zhen Wang
- Departments of Structural Biology and Developmental Neurobiology
| | - Yingxue Fu
- Departments of Structural Biology and Developmental Neurobiology
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USA
| | | | - Thomas G. Beach
- Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology
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22
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Hamza GM, Raghunathan R, Ashenden S, Zhang B, Miele E, Jarnuczak AF. Proteomics of prostate cancer serum and plasma using low and high throughput approaches. Clin Proteomics 2024; 21:21. [PMID: 38475692 DOI: 10.1186/s12014-024-09461-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.
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Affiliation(s)
| | - Rekha Raghunathan
- Bioanalytical and Biomarker, Prevail Therapeutics, Wholly Owned Subsidiary of Eli Lilly and Company, New York, NY, 10016, USA
| | | | - Bairu Zhang
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Eric Miele
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
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23
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Hsiao Y, Zhang H, Li GX, Deng Y, Yu F, Kahrood HV, Steele JR, Schittenhelm RB, Nesvizhskii AI. Analysis and visualization of quantitative proteomics data using FragPipe-Analyst. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.05.583643. [PMID: 38496650 PMCID: PMC10942459 DOI: 10.1101/2024.03.05.583643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.
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Affiliation(s)
- Yi Hsiao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Haijian Zhang
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yamei Deng
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hossein Valipour Kahrood
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
- Monash Genomics & Bioinformatics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Joel R. Steele
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Ralf B. Schittenhelm
- Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
| | - Alexey I. Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
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24
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Burton JB, Silva-Barbosa A, Bons J, Rose J, Pfister K, Simona F, Gandhi T, Reiter L, Bernhardt O, Hunter CL, Goetzman ES, Sims-Lucas S, Schilling B. Substantial downregulation of mitochondrial and peroxisomal proteins during acute kidney injury revealed by data-independent acquisition proteomics. Proteomics 2024; 24:e2300162. [PMID: 37775337 DOI: 10.1002/pmic.202300162] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 10/01/2023]
Abstract
Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A ZenoTOF 7600 mass spectrometer was optimized for data-independent acquisition (DIA) to achieve comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured kidneys exhibited severely damaged tissues and injury markers. The comprehensive and sensitive kidney-specific DIA-MS assays feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome, and will serve as useful tools for developing novel therapeutics to remediate kidney function.
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Affiliation(s)
- Jordan B Burton
- Buck Institute for Research on Aging, Novato, California, USA
| | - Anne Silva-Barbosa
- Department of Pediatrics, School of Medicine, Medical Center Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Joanna Bons
- Buck Institute for Research on Aging, Novato, California, USA
| | - Jacob Rose
- Buck Institute for Research on Aging, Novato, California, USA
| | - Katherine Pfister
- Department of Pediatrics, School of Medicine, Medical Center Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | | | | | | | | | - Eric S Goetzman
- Department of Pediatrics, School of Medicine, Medical Center Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Sunder Sims-Lucas
- Department of Pediatrics, School of Medicine, Medical Center Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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25
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Hartley B, Bassiouni W, Roczkowsky A, Fahlman R, Schulz R, Julien O. Data-Independent Acquisition Proteomics and N-Terminomics Methods Reveal Alterations in Mitochondrial Function and Metabolism in Ischemic-Reperfused Hearts. J Proteome Res 2024; 23:844-856. [PMID: 38264990 PMCID: PMC10846531 DOI: 10.1021/acs.jproteome.3c00754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 01/06/2024] [Accepted: 01/10/2024] [Indexed: 01/25/2024]
Abstract
Myocardial ischemia-reperfusion (IR) (stunning) injury triggers changes in the proteome and degradome of the heart. Here, we utilize quantitative proteomics and comprehensive degradomics to investigate the molecular mechanisms of IR injury in isolated rat hearts. The control group underwent aerobic perfusion, while the IR injury group underwent 20 min of ischemia and 30 min of reperfusion to induce a stunning injury. As MMP-2 activation has been shown to contribute to myocardial injury, hearts also underwent IR injury with ARP-100, an MMP-2-preferring inhibitor, to dissect the contribution of MMP-2 to IR injury. Using data-independent acquisition (DIA) and mass spectroscopy, we quantified 4468 proteins in ventricular extracts, whereby 447 proteins showed significant alterations among the three groups. We then used subtiligase-mediated N-terminomic labeling to identify more than a hundred specific cleavage sites. Among these protease substrates, 15 were identified following IR injury. We identified alterations in numerous proteins involved in mitochondrial function and metabolism following IR injury. Our findings provide valuable insights into the biochemical mechanisms of myocardial IR injury, suggesting alterations in reactive oxygen/nitrogen species handling and generation, fatty acid metabolism, mitochondrial function and metabolism, and cardiomyocyte contraction.
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Affiliation(s)
- Bridgette Hartley
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
| | - Wesam Bassiouni
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
| | - Andrej Roczkowsky
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
| | - Richard Fahlman
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
| | - Richard Schulz
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
- Department
of Pediatrics, University of Alberta, Edmonton T6G 2S2, Canada
| | - Olivier Julien
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
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26
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Lou R, Shui W. Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023. Mol Cell Proteomics 2024; 23:100712. [PMID: 38182042 PMCID: PMC10847697 DOI: 10.1016/j.mcpro.2024.100712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/27/2023] [Accepted: 01/02/2024] [Indexed: 01/07/2024] Open
Abstract
Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.
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Affiliation(s)
- Ronghui Lou
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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27
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Gobom J, Brinkmalm A, Brinkmalm G, Blennow K, Zetterberg H. Alzheimer's Disease Biomarker Analysis Using Targeted Mass Spectrometry. Mol Cell Proteomics 2024; 23:100721. [PMID: 38246483 PMCID: PMC10926085 DOI: 10.1016/j.mcpro.2024.100721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/30/2023] [Accepted: 01/04/2024] [Indexed: 01/23/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by several neuropathological changes, mainly extracellular amyloid aggregates (plaques), intraneuronal inclusions of phosphorylated tau (tangles), as well as neuronal and synaptic degeneration, accompanied by tissue reactions to these processes (astrocytosis and microglial activation) that precede neuronal network disturbances in the symptomatic phase of the disease. A number of biomarkers for these brain tissue changes have been developed, mainly using immunoassays. In this review, we discuss how targeted mass spectrometry (TMS) can be used to validate and further characterize classes of biomarkers reflecting different AD pathologies, such as tau- and amyloid-beta pathologies, synaptic dysfunction, lysosomal dysregulation, and axonal damage, and the prospect of using TMS to measure these proteins in clinical research and diagnosis. TMS advantages and disadvantages in relation to immunoassays are discussed, and complementary aspects of the technologies are discussed.
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Affiliation(s)
- Johan Gobom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
| | - Ann Brinkmalm
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Gunnar Brinkmalm
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA.
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28
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Jafari A, Farahani M, Abdollahpour-Alitappeh M, Manzari-Tavakoli A, Yazdani M, Rezaei-Tavirani M. Unveiling diagnostic and therapeutic strategies for cervical cancer: biomarker discovery through proteomics approaches and exploring the role of cervical cancer stem cells. Front Oncol 2024; 13:1277772. [PMID: 38328436 PMCID: PMC10847843 DOI: 10.3389/fonc.2023.1277772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 12/27/2023] [Indexed: 02/09/2024] Open
Abstract
Cervical cancer (CC) is a major global health problem and leading cause of cancer deaths among women worldwide. Early detection through screening programs has reduced mortality; however, screening compliance remains low. Identifying non-invasive biomarkers through proteomics for diagnosis and monitoring response to treatment could improve patient outcomes. Here we review recent proteomics studies which have uncovered biomarkers and potential drug targets for CC. Additionally, we explore into the role of cervical cancer stem cells and their potential implications in driving CC progression and therapy resistance. Although challenges remain, proteomics has the potential to revolutionize the field of cervical cancer research and improve patient outcomes.
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Affiliation(s)
- Ameneh Jafari
- Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Masoumeh Farahani
- Skin Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Asma Manzari-Tavakoli
- Department of Biology, Faculty of Science, Rayan Center for Neuroscience and Behavior, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Mohsen Yazdani
- Laboratory of Bioinformatics and Drug Design, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
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29
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Dowling P, Trollet C, Negroni E, Swandulla D, Ohlendieck K. How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction? Proteomes 2024; 12:4. [PMID: 38250815 PMCID: PMC10801633 DOI: 10.3390/proteomes12010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/09/2024] [Accepted: 01/12/2024] [Indexed: 01/23/2024] Open
Abstract
This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.
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Affiliation(s)
- Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Capucine Trollet
- Center for Research in Myology U974, Sorbonne Université, INSERM, Myology Institute, 75013 Paris, France; (C.T.); (E.N.)
| | - Elisa Negroni
- Center for Research in Myology U974, Sorbonne Université, INSERM, Myology Institute, 75013 Paris, France; (C.T.); (E.N.)
| | - Dieter Swandulla
- Institute of Physiology, Faculty of Medicine, University of Bonn, D53115 Bonn, Germany;
| | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
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30
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Abhange K, Kitata RB, Zhang J, Wang YT, Gaffrey MJ, Liu T, Gunchick V, Khaykin V, Sahai V, Cuneo KC, Parikh ND, Shi T, Lubman DM. In-Depth Proteome Profiling of Small Extracellular Vesicles Isolated from Cancer Cell Lines and Patient Serum. J Proteome Res 2024; 23:386-396. [PMID: 38113368 PMCID: PMC10947532 DOI: 10.1021/acs.jproteome.3c00614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Extracellular vesicle (EV) secretion has been observed in many types of both normal and tumor cells. EVs contain a variety of distinctive cargoes, allowing tumor-derived serum proteins in EVs to act as a minimally invasive method for clinical monitoring. We have undertaken a comprehensive study of the protein content of the EVs from several cancer cell lines using direct data-independent analysis. Several thousand proteins were detected, including many classic EV markers such as CD9, CD81, CD63, TSG101, and Syndecan-1, among others. We detected many distinctive cancer-specific proteins, including several known markers used in cancer detection and monitoring. We further studied the protein content of EVs from patient serum for both normal controls and pancreatic cancer and hepatocellular carcinoma. The EVs for these studies have been isolated by various methods for comparison, including ultracentrifugation and CD9 immunoaffinity column. Typically, 500-1000 proteins were identified, where most of them overlapped with the EV proteins identified from the cell lines studied. We were able to identify many of the cell-line EV protein markers in the serum EVs, in addition to the large numbers of proteins specific to pancreatic and HCC cancers.
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Affiliation(s)
- Komal Abhange
- Department of Surgery, University of Michigan Medical Center, Ann Arbor, Michigan 48109, United States
| | - Reta Birhanu Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jie Zhang
- Department of Surgery, University of Michigan Medical Center, Ann Arbor, Michigan 48109, United States
| | - Yi-Ting Wang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Matthew J Gaffrey
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Valerie Gunchick
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Valerie Khaykin
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Vaibhav Sahai
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Kyle C Cuneo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Neehar D Parikh
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - David M Lubman
- Department of Surgery, University of Michigan Medical Center, Ann Arbor, Michigan 48109, United States
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31
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Huang M, Zheng X, Zhang Y, Wang R, Wei X. Comparative proteomics analysis of kidney in chicken infected by infectious bronchitis virus. Poult Sci 2024; 103:103259. [PMID: 37992619 PMCID: PMC10700468 DOI: 10.1016/j.psj.2023.103259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 10/25/2023] [Accepted: 11/02/2023] [Indexed: 11/24/2023] Open
Abstract
The gamma coronavirus infectious bronchitis virus (IBV) is known to cause an acute and highly contagious infectious disease in poultry. Here, this study aimed to investigate the impact of virulent or avirulent IBV infection on the avian host by conducting proteomics with data-independent acquisition mass spectrometry (DIA-MS) in the kidneys of IBV-infected chickens. The results revealed 267, 489, and 510 differentially expressed proteins (DEPs) in the chicken kidneys at 3, 5, and 7 days postinfection (dpi), respectively, when infected with the GD17/04 strain, which is a highly nephrogenic strain and belongs to the 4/91 genotype. In contrast, the attenuated 4/91 vaccine resulted in the identification of 144, 175, and 258 DEPs at 3, 5, and 7 dpi, respectively. Functional enrichment analyses indicated distinct expression profiles between the 2 IBV strains. Upon GD17/04 infection, metabolic pathways respond initially in the early stage (3 dpi) and immune-related signaling pathways respond in the middle and late stages (5 and 7 dpi). The 4/91 vaccine elicited a completely opposite response compared to the GD17/04 infection. Among all DEPs, 62 immune-related DEPs were focused on and found to be mainly enriched in the type I interferon (IFN-I) signaling pathway and involved in humoral and cellular immunity. Notably, key molecules in the IFN-I signaling pathway including MDA5, LGP2, and TBK1 may serve as regulatory targets of IBV. Overall, this study highlights similarities and discrepancies in the patterns of protein expression at different stages of infection with virulent and avirulent IBV strains, with the IFN-I signaling pathway emerging as a critical response to IBV infection.
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Affiliation(s)
- Mengjiao Huang
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
| | - Xuewei Zheng
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China
| | - Yunjing Zhang
- National Research Center for Veterinary Medicine, Luoyang 471000, China
| | - Ruohan Wang
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China
| | - Xiaona Wei
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, China
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32
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Xiang P, Liyu A, Kwon Y, Hu D, Williams SM, Veličković D, Markillie LM, Chrisler WB, Paša-Tolić L, Zhu Y. Spatial Proteomics toward Subcellular Resolution by Coupling Deep Ultraviolet Laser Ablation with Nanodroplet Sample Preparation. ACS MEASUREMENT SCIENCE AU 2023; 3:459-468. [PMID: 38145026 PMCID: PMC10740121 DOI: 10.1021/acsmeasuresciau.3c00033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/17/2023] [Accepted: 09/22/2023] [Indexed: 12/26/2023]
Abstract
Multiplexed molecular profiling of tissue microenvironments, or spatial omics, can provide critical insights into cellular functions and disease pathology. The coupling of laser microdissection with mass spectrometry-based proteomics has enabled deep and unbiased mapping of >1000 proteins. However, the throughput of laser microdissection is often limited due to tedious two-step procedures, sequential laser cutting, and sample collection. The two-step procedure also hinders the further improvement of spatial resolution to <10 μm as needed for subcellular proteomics. Herein, we developed a high-throughput and high-resolution spatial proteomics platform by seamlessly coupling deep ultraviolet (DUV) laser ablation (LA) with nanoPOTS (Nanodroplet Processing in One pot for Trace Samples)-based sample preparation. We demonstrated the DUV-LA system can quickly isolate and collect tissue samples at a throughput of ∼30 spots/min and a spatial resolution down to 2 μm from a 10 μm thick human pancreas tissue section. To improve sample recovery, we developed a proximity aerosol collection approach by placing DMSO droplets close to LA spots. We demonstrated the DUV-LA-nanoPOTS platform can detect an average of 1312, 1533, and 1966 proteins from ablation spots with diameters of 7, 13, and 19 μm, respectively. In a proof-of-concept study, we isolated and profiled two distinct subcellular regions of the pancreas tissue revealed by hematoxylin and eosin (H&E) staining. Quantitative proteomics revealed proteins specifically enriched to subcellular compartments.
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Affiliation(s)
- Piliang Xiang
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Andrey Liyu
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Yumi Kwon
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Dehong Hu
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Sarah M. Williams
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Dušan Veličković
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Lye Meng Markillie
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - William B. Chrisler
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99354, United States
| | - Ljiljana Paša-Tolić
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Ying Zhu
- Department
of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
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33
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Zhang L, Xu F, Lu H, Dong X, Gao Z, Zhao Q, Weng T, Li H, Ye H. Data-independent acquisition (DIA) mass spectrometry reveals related proteins involved in the occurrence of early intestinal-type gastric cancer. Med Oncol 2023; 41:23. [PMID: 38114688 DOI: 10.1007/s12032-023-02241-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 11/07/2023] [Indexed: 12/21/2023]
Abstract
Identifying proteins associated with the onset of early intestinal-type gastric cancer (EIGC) can yield valuable insights into the pathogenesis of this specific subtype of gastric cancer. Data-independent acquisition mass spectroscopy (DIA-MS) was utilized to identify the differential protein between 10 cases of EIGC and atrophic gastritis with intestinal metaplasia (NGC). The expressions of IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were verified by immunohistochemistry (IHC) in 20 EIGC samples, 17 gastric low-grade intraepithelial neoplasia (LGIN) samples, and 21 healthy controls. The prognostic values of the five genes were validated in the transcriptome data by survival analysis. A total of 4,028 proteins were identified using DIA-MS and a total of 177 differential proteins were screened with log2(fold change) > 1.5. Among them, 113 proteins were significantly up-regulated, and 64 proteins were significantly down-regulated in EIGC tissues. IHC results showed that proteins IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were highly expressed in the cytoplasm of EIGC and LGIN, which was consistent with the results of DIA-MS. Among them, p62/SQSTM1 may undergo nuclear-cytoplasmic transfer. The five protein-coding genes were associated with intestinal-type gastric cancer survival and exhibited differential expression across various disease stages. The study successfully identified differentially expressed proteins between EIGC and NGC, providing potential biomarkers and valuable insights into the mechanism underlying intestinal-type gastric cancer.
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Affiliation(s)
- Liangshun Zhang
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Feng Xu
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Hongna Lu
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Xianwen Dong
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Zhiqiang Gao
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Qiaosu Zhao
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Ting Weng
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China
| | - Hong Li
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China.
| | - Hua Ye
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315046, Zhejiang, People's Republic of China.
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Borteçen T, Müller T, Krijgsveld J. An integrated workflow for quantitative analysis of the newly synthesized proteome. Nat Commun 2023; 14:8237. [PMID: 38086798 PMCID: PMC10716174 DOI: 10.1038/s41467-023-43919-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
The analysis of proteins that are newly synthesized upon a cellular perturbation can provide detailed insight into the proteomic response that is elicited by specific cues. This can be investigated by pulse-labeling of cells with clickable and stable-isotope-coded amino acids for the enrichment and mass spectrometric characterization of newly synthesized proteins (NSPs), however convoluted protocols prohibit their routine application. Here we report the optimization of multiple steps in sample preparation, mass spectrometry and data analysis, and we integrate them into a semi-automated workflow for the quantitative analysis of the newly synthesized proteome (QuaNPA). Reduced input requirements and data-independent acquisition (DIA) enable the analysis of triple-SILAC-labeled NSP samples, with enhanced throughput while featuring high quantitative accuracy. We apply QuaNPA to investigate the time-resolved cellular response to interferon-gamma (IFNg), observing rapid induction of targets 2 h after IFNg treatment. QuaNPA provides a powerful approach for large-scale investigation of NSPs to gain insight into complex cellular processes.
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Affiliation(s)
- Toman Borteçen
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, Heidelberg, Germany
- Heidelberg University, Faculty of Biosciences, Im Neuenheimer Feld 581, Heidelberg, Germany
| | - Torsten Müller
- Heidelberg University, Medical Faculty, Im Neuenheimer Feld 581, Heidelberg, Germany
| | - Jeroen Krijgsveld
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, Heidelberg, Germany.
- Heidelberg University, Medical Faculty, Im Neuenheimer Feld 581, Heidelberg, Germany.
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35
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Stair ER, Hicks LM. Recent advances in mass spectrometry-based methods to investigate reversible cysteine oxidation. Curr Opin Chem Biol 2023; 77:102389. [PMID: 37776664 DOI: 10.1016/j.cbpa.2023.102389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/10/2023] [Accepted: 08/31/2023] [Indexed: 10/02/2023]
Abstract
The post-translational modification of cysteine to diverse oxidative states is understood as a critical cellular mechanism to combat oxidative stress. To study the role of cysteine oxidation, cysteine enrichments and subsequent analysis via mass spectrometry are necessary. As such, technologies and methods are rapidly developing for sensitive and efficient enrichments of cysteines to further explore its role in signaling pathways. In this review, we analyze recent developments in methods to miniaturize cysteine enrichments, analyze the underexplored disulfide bound redoxome, and quantify site-specific cysteine oxidation. We predict that further development of these methods will improve cysteine coverage across more diverse organisms than those previously studied and elicit novel roles cysteines play in stress response.
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Affiliation(s)
- Evan R Stair
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Leslie M Hicks
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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36
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Huang J, Staes A, Impens F, Demichev V, Van Breusegem F, Gevaert K, Willems P. CysQuant: Simultaneous quantification of cysteine oxidation and protein abundance using data dependent or independent acquisition mass spectrometry. Redox Biol 2023; 67:102908. [PMID: 37793239 PMCID: PMC10562924 DOI: 10.1016/j.redox.2023.102908] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 09/20/2023] [Accepted: 09/26/2023] [Indexed: 10/06/2023] Open
Abstract
Protein cysteinyl thiols are susceptible to reduction-oxidation reactions that can influence protein function. Accurate quantification of cysteine oxidation is therefore crucial for decoding protein redox regulation. Here, we present CysQuant, a novel approach for simultaneous quantification of cysteine oxidation degrees and protein abundancies. CysQuant involves light/heavy iodoacetamide isotopologues for differential labeling of reduced and reversibly oxidized cysteines analyzed by data-dependent acquisition (DDA) or data-independent acquisition mass spectrometry (DIA-MS). Using plexDIA with in silico predicted spectral libraries, we quantified an average of 18% cysteine oxidation in Arabidopsis thaliana by DIA-MS, including a subset of highly oxidized cysteines forming disulfide bridges in AlphaFold2 predicted structures. Applying CysQuant to Arabidopsis seedlings exposed to excessive light, we successfully quantified the well-established increased reduction of Calvin-Benson cycle enzymes and discovered yet uncharacterized redox-sensitive disulfides in chloroplastic enzymes. Overall, CysQuant is a highly versatile tool for assessing the cysteine modification status that can be widely applied across various mass spectrometry platforms and organisms.
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Affiliation(s)
- Jingjing Huang
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium; Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - An Staes
- Department of Biomolecular Medicine, Ghent University, 9052, Ghent, Belgium; Center for Medical Biotechnology, VIB, 9052, Ghent, Belgium; VIB Proteomics Core, 9052, Ghent, Belgium
| | - Francis Impens
- Department of Biomolecular Medicine, Ghent University, 9052, Ghent, Belgium; Center for Medical Biotechnology, VIB, 9052, Ghent, Belgium; VIB Proteomics Core, 9052, Ghent, Belgium
| | - Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, 10117, Berlin, Germany
| | - Frank Van Breusegem
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium; Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - Kris Gevaert
- Department of Biomolecular Medicine, Ghent University, 9052, Ghent, Belgium; Center for Medical Biotechnology, VIB, 9052, Ghent, Belgium.
| | - Patrick Willems
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium; Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, 9052, Ghent, Belgium; Center for Medical Biotechnology, VIB, 9052, Ghent, Belgium.
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37
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Dowling P, Swandulla D, Ohlendieck K. Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology. Cells 2023; 12:2560. [PMID: 37947638 PMCID: PMC10649384 DOI: 10.3390/cells12212560] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 10/27/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023] Open
Abstract
Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.
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Affiliation(s)
- Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Dieter Swandulla
- Institute of Physiology, Faculty of Medicine, University of Bonn, D53115 Bonn, Germany;
| | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland;
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
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38
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Stepler KE, Hannah SC, Taneyhill LA, Nemes P. Deep Proteome of the Developing Chick Midbrain. J Proteome Res 2023; 22:3264-3274. [PMID: 37616547 DOI: 10.1021/acs.jproteome.3c00291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
The epithelial-to-mesenchymal transition (EMT) and migration of cranial neural crest cells within the midbrain are critical processes that permit proper craniofacial patterning in the early embryo. Disruptions in these processes not only impair development but also lead to various diseases, underscoring the need for their detailed understanding at the molecular level. The chick embryo has served historically as an excellent model for human embryonic development, including cranial neural crest cell EMT and migration. While these developmental events have been characterized transcriptionally, studies at the protein level have not been undertaken to date. Here, we applied mass spectrometry (MS)-based proteomics to establish a deep proteomics profile of the chick midbrain region during early embryonic development. Our proteomics method combines optimal lysis conditions, offline fractionation, separation on a nanopatterned stationary phase (μPAC) using nanoflow liquid chromatography, and detection using quadrupole-ion trap-Orbitrap tribrid high-resolution tandem MS. Identification of >5900 proteins and >450 phosphoproteins in this study marks the deepest coverage of the chick midbrain proteome to date. These proteins have known roles in pathways related to neural crest cell EMT and migration such as signaling, proteolysis/extracellular matrix remodeling, and transcriptional regulation. This study offers valuable insight into important developmental processes occurring in the midbrain region and demonstrates the utility of proteomics for characterization of tissue microenvironments during chick embryogenesis.
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Affiliation(s)
- Kaitlyn E Stepler
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
| | - Seth C Hannah
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Lisa A Taneyhill
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
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39
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Edsjö A, Holmquist L, Geoerger B, Nowak F, Gomon G, Alix-Panabières C, Ploeger C, Lassen U, Le Tourneau C, Lehtiö J, Ott PA, von Deimling A, Fröhling S, Voest E, Klauschen F, Dienstmann R, Alshibany A, Siu LL, Stenzinger A. Precision cancer medicine: Concepts, current practice, and future developments. J Intern Med 2023; 294:455-481. [PMID: 37641393 DOI: 10.1111/joim.13709] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.
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Affiliation(s)
- Anders Edsjö
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
- Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
- Genomic Medicine Sweden (GMS), Kristianstad, Sweden
| | - Louise Holmquist
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
- Genomic Medicine Sweden (GMS), Kristianstad, Sweden
| | - Birgit Geoerger
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | | | - Georgy Gomon
- Department of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Department of Medical Oncology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Catherine Alix-Panabières
- Laboratory of Rare Human Circulating Cells, University Medical Center of Montpellier, Montpellier, France
- CREEC, MIVEGEC, University of Montpellier, Montpellier, France
| | - Carolin Ploeger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Centers for Personalized Medicine (ZPM), Heidelberg, Germany
| | - Ulrik Lassen
- Department of Oncology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Christophe Le Tourneau
- Department of Drug Development and Innovation (D3i), Institut Curie, Paris, France
- INSERM U900 Research Unit, Saint-Cloud, France
- Faculty of Medicine, Paris-Saclay University, Paris, France
| | - Janne Lehtiö
- Department of Oncology Pathology, Karolinska Institutet, Science for Life Laboratory, Stockholm, Sweden
| | - Patrick A Ott
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
| | - Andreas von Deimling
- Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Stefan Fröhling
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Emile Voest
- Department of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Frederick Klauschen
- Institute of Pathology, Charite - Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
- Institute of Pathology, Ludwig-Maximilians-University, Munich, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Munich Partner Site, Heidelberg, Germany
| | | | | | - Lillian L Siu
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Albrecht Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Centers for Personalized Medicine (ZPM), Heidelberg, Germany
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40
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Li X. Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing. J Pharm Biomed Anal 2023; 234:115581. [PMID: 37494866 DOI: 10.1016/j.jpba.2023.115581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/27/2023] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.
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Affiliation(s)
- Xuanwen Li
- Analytical Research and Development, MRL, Merck & Co., Inc., 126 E. Lincoln Avenue, Rahway, NJ 07065, USA.
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41
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Kazdal D, Menzel M, Budczies J, Stenzinger A. [Molecular tumor diagnostics as the driving force behind precision oncology]. Dtsch Med Wochenschr 2023; 148:1157-1165. [PMID: 37657453 DOI: 10.1055/a-1937-0347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/03/2023]
Abstract
Molecular pathological diagnostics plays a central role in personalized oncology and requires multidisciplinary teamwork. It is just as relevant for the individual patient who is being treated with an approved therapy method or an individual treatment attempt as it is for prospective clinical studies that require the identification of specific therapeutic target structures or complex biomarkers for study inclusion. It is also of crucial importance for the generation of real-world data, which is becoming increasingly important for drug development. Future developments will be significantly shaped by improvements in scalable molecular diagnostics, in which increasingly complex and multi-layered data sets must be quickly converted into clinically useful information. One focus will be on the development of adaptive diagnostic strategies in order to be able to depict the enormous plasticity of a cancer disease over time.
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42
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George AL, Sidgwick FR, Watt JE, Martin MP, Trost M, Marín-Rubio JL, Dueñas ME. Comparison of Quantitative Mass Spectrometric Methods for Drug Target Identification by Thermal Proteome Profiling. J Proteome Res 2023; 22:2629-2640. [PMID: 37439223 PMCID: PMC10407934 DOI: 10.1021/acs.jproteome.3c00111] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Indexed: 07/14/2023]
Abstract
Thermal proteome profiling (TPP) provides a powerful approach to studying proteome-wide interactions of small therapeutic molecules and their target and off-target proteins, complementing phenotypic-based drug screens. Detecting differences in thermal stability due to target engagement requires high quantitative accuracy and consistent detection. Isobaric tandem mass tags (TMTs) are used to multiplex samples and increase quantification precision in TPP analysis by data-dependent acquisition (DDA). However, advances in data-independent acquisition (DIA) can provide higher sensitivity and protein coverage with reduced costs and sample preparation steps. Herein, we explored the performance of different DIA-based label-free quantification approaches compared to TMT-DDA for thermal shift quantitation. Acute myeloid leukemia cells were treated with losmapimod, a known inhibitor of MAPK14 (p38α). Label-free DIA approaches, and particularly the library-free mode in DIA-NN, were comparable of TMT-DDA in their ability to detect target engagement of losmapimod with MAPK14 and one of its downstream targets, MAPKAPK3. Using DIA for thermal shift quantitation is a cost-effective alternative to labeled quantitation in the TPP pipeline.
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Affiliation(s)
- Amy L. George
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Frances R. Sidgwick
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Jessica E. Watt
- Newcastle
Cancer Centre, Northern Institute for Cancer Research, Medical School, Newcastle University, Paul O’Gorman Building, Framlington Place, Newcastle upon Tyne NE2 4HH, U.K.
| | - Mathew P. Martin
- Newcastle
Cancer Centre, Northern Institute for Cancer Research, Medical School, Newcastle University, Paul O’Gorman Building, Framlington Place, Newcastle upon Tyne NE2 4HH, U.K.
| | - Matthias Trost
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - José Luis Marín-Rubio
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Maria Emilia Dueñas
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
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Yang KL, Yu F, Teo GC, Li K, Demichev V, Ralser M, Nesvizhskii AI. MSBooster: improving peptide identification rates using deep learning-based features. Nat Commun 2023; 14:4539. [PMID: 37500632 PMCID: PMC10374903 DOI: 10.1038/s41467-023-40129-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 07/06/2023] [Indexed: 07/29/2023] Open
Abstract
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.
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Affiliation(s)
- Kevin L Yang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Markus Ralser
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Nuffield Department of Medicine, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
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Yu F, Teo GC, Kong AT, Fröhlich K, Li GX, Demichev V, Nesvizhskii AI. Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform. Nat Commun 2023; 14:4154. [PMID: 37438352 PMCID: PMC10338508 DOI: 10.1038/s41467-023-39869-5] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/28/2023] [Indexed: 07/14/2023] Open
Abstract
Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
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Affiliation(s)
- Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Andy T Kong
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Klemens Fröhlich
- Proteomics Core Facility, Biozentrum, University of Basel, Basel, Switzerland
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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Dowling P, Gargan S, Zweyer M, Swandulla D, Ohlendieck K. Extracellular Matrix Proteomics: The mdx-4cv Mouse Diaphragm as a Surrogate for Studying Myofibrosis in Dystrophinopathy. Biomolecules 2023; 13:1108. [PMID: 37509144 PMCID: PMC10377647 DOI: 10.3390/biom13071108] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
The progressive degeneration of the skeletal musculature in Duchenne muscular dystrophy is accompanied by reactive myofibrosis, fat substitution, and chronic inflammation. Fibrotic changes and reduced tissue elasticity correlate with the loss in motor function in this X-chromosomal disorder. Thus, although dystrophinopathies are due to primary abnormalities in the DMD gene causing the almost-complete absence of the cytoskeletal Dp427-M isoform of dystrophin in voluntary muscles, the excessive accumulation of extracellular matrix proteins presents a key histopathological hallmark of muscular dystrophy. Animal model research has been instrumental in the characterization of dystrophic muscles and has contributed to a better understanding of the complex pathogenesis of dystrophinopathies, the discovery of new disease biomarkers, and the testing of novel therapeutic strategies. In this article, we review how mass-spectrometry-based proteomics can be used to study changes in key components of the endomysium, perimysium, and epimysium, such as collagens, proteoglycans, matricellular proteins, and adhesion receptors. The mdx-4cv mouse diaphragm displays severe myofibrosis, making it an ideal model system for large-scale surveys of systematic alterations in the matrisome of dystrophic fibers. Novel biomarkers of myofibrosis can now be tested for their appropriateness in the preclinical and clinical setting as diagnostic, pharmacodynamic, prognostic, and/or therapeutic monitoring indicators.
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Affiliation(s)
- Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Stephen Gargan
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Margit Zweyer
- Department of Neonatology and Paediatric Intensive Care, Children's Hospital, German Center for Neurodegenerative Diseases, University of Bonn, D53127 Bonn, Germany
| | - Dieter Swandulla
- Institute of Physiology, Medical Faculty, University of Bonn, D53115 Bonn, Germany
| | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
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Burton JB, Silva-Barbosa A, Bons J, Rose J, Pfister K, Simona F, Gandhi T, Reiter L, Bernhardt O, Hunter CL, Goetzman ES, Sims-Lucas S, Schilling B. Substantial Downregulation of Mitochondrial and Peroxisomal Proteins during Acute Kidney Injury revealed by Data-Independent Acquisition Proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.26.530107. [PMID: 36865241 PMCID: PMC9980295 DOI: 10.1101/2023.02.26.530107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A fast-acquisition rate ZenoTOF 7600 mass spectrometer was introduced for data-independent acquisition (DIA) for comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3,945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured mice exhibited severely declined health. The comprehensive and sensitive kidney-specific DIA assays highlighted here feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome and will serve as useful tools for developing novel therapeutics to remediate kidney function.
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Dowling P, Gargan S, Swandulla D, Ohlendieck K. Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles. Int J Mol Sci 2023; 24:2415. [PMID: 36768735 PMCID: PMC9916839 DOI: 10.3390/ijms24032415] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/20/2023] [Accepted: 01/23/2023] [Indexed: 01/28/2023] Open
Abstract
The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.
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Affiliation(s)
- Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Stephen Gargan
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
| | - Dieter Swandulla
- Institute of Physiology, University of Bonn, D53115 Bonn, Germany
| | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, W23 F2H6 Maynooth, Co. Kildare, Ireland
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, W23 F2H6 Maynooth, Co. Kildare, Ireland
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Wang Y, Xi W, Zhang X, Bi X, Liu B, Zheng X, Chi X. CTSB promotes sepsis-induced acute kidney injury through activating mitochondrial apoptosis pathway. Front Immunol 2023; 13:1053754. [PMID: 36713420 PMCID: PMC9880165 DOI: 10.3389/fimmu.2022.1053754] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023] Open
Abstract
Background Acute kidney injury is a common and severe complication of sepsis. Sepsis -induced acute kidney injury(S-AKI) is an independent risk factor for mortality among sepsis patients. However, the mechanisms of S-AKI are complex and poorly understand. Therefore, exploring the underlying mechanisms of S-AKI may lead to the development of therapeutic targets. Method A model of S-AKI was established in male C57BL/6 mice using cecal ligation and puncture (CLP). The data-independent acquisition (DIA)-mass spectrometry-based proteomics was used to explore the protein expression changes and analyze the key proteomics profile in control and CLP group. The methodology was also used to identify the key proteins and pathways. S-AKI in vitro was established by treating the HK-2 cells with lipopolysaccharide (LPS). Subsequently, the effect and mechanism of Cathepsin B (CTSB) in inducing apoptosis in HK-2 cells were observed and verified. Results The renal injury scores, serum creatinine, blood urea nitrogen, and kidney injury molecule 1 were higher in septic mice than in non-septic mice. The proteomic analysis identified a total of 449 differentially expressed proteins (DEPs). GO and KEGG analysis showed that DEPs were mostly enriched in lysosomal-related cell structures and pathways. CTSB and MAPK were identified as key proteins in S-AKI. Electron microscopy observed enlarged lysosomes, swelled and ruptured mitochondria, and cytoplasmic vacuolization in CLP group. TUNEL staining and CTSB activity test showed that the apoptosis and CTSB activity were higher in CLP group than in control group. In HK-2 cell injury model, the CTSB activity and mRNA expression were increased in LPS-treated cells. Acridine orange staining showed that LPS caused lysosomal membrane permeabilization (LMP). CA074 as an inhibitor of CTSB could effectively inhibit CTSB activity. CCK8 and Annexin V/PI staining results indicated that CA074 reversed LPS-induced apoptosis of HK-2 cells. The JC-1 and western blot results showed that LPS inhibited mitochondrial membrane potential and activated mitochondrial apoptosis pathway, which could be reversed by CA074. Conclusions LMP and CTSB contribute to pathogenesis of S-AKI. LPS treatment induced HK-2 cell injury by activating mitochondrial apoptosis pathway. Inhibition of CTSB might be a new therapeutic strategy to alleviate sepsis-induced acute kidney injury.
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Affiliation(s)
- Yuting Wang
- Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Wenjie Xi
- Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Xinyi Zhang
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Xinwen Bi
- Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Boyang Liu
- Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Xiaoming Zheng
- Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China,*Correspondence: Xiaoming Zheng, ; Xinjin Chi,
| | - Xinjin Chi
- Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China,*Correspondence: Xiaoming Zheng, ; Xinjin Chi,
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Yu S, Li X, Xin Z, Sun L, Shi J. Proteomic insights into SARS-CoV-2 infection mechanisms, diagnosis, therapies and prognostic monitoring methods. Front Immunol 2022; 13:923387. [PMID: 36203586 PMCID: PMC9530739 DOI: 10.3389/fimmu.2022.923387] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 09/05/2022] [Indexed: 01/08/2023] Open
Abstract
At the end of 2019, the COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection, seriously damaged world public health security. Several protein markers associated with virus infection have been extensively explored to combat the ever-increasing challenge posed by SARS-CoV-2. The proteomics of COVID-19 deepened our understanding of viral particles and their mechanisms of host invasion, providing us with information on protein changes in host tissues, cells and body fluids following infection in COVID-19 patients. In this review, we summarize the proteomic studies of SARS-CoV-2 infection and review the current understanding of COVID-19 in terms of the quantitative and qualitative proteomics of viral particles and host entry factors from the perspective of protein pathological changes in the organism following host infection.
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Affiliation(s)
- Shengman Yu
- Department of Laboratory Medicine Center, China-Japan Union Hospital, Jilin University, Changchun, China
- School of Laboratory Medicine, Beihua University, Jilin, China
| | - Xiaoyan Li
- Department of Infection Control Department, Hospital of Stomatology, Jilin University, Changchun, China
| | - Zhuoyuan Xin
- The Key Laboratory of Zoonosis Research, Chinese Ministry of Education, College of Basic Medical Science, Jilin University, Changchun, China
| | - Liyuan Sun
- School of Laboratory Medicine, Beihua University, Jilin, China
| | - Jingwei Shi
- Department of Laboratory Medicine Center, China-Japan Union Hospital, Jilin University, Changchun, China
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